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limits map which describes the performance of a turbine wheel with respect to the microstructure through simulation and empirical testing. The aim of the project is to develop a modelling and simulation
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Multiple self-funded PhD positions are available in Modelling and Simulation (M&S). The project will aim to mature software repositories describing the biomechanics of the human brain. The M&S tools
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to the development of multiscale computational models for simulating crack propagation and establishing reliable methods to predict the residual strength of composite structures. The simulations, performed in Ansys
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Current modelling and simulations require either generic assumptions to be made for fluid dynamic based modelling leading to inaccuracies between modelled and experimental data or, intense
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& environmental risk assessment. Numerical simulation techniques for hydrogeological systems. Advanced uncertainty quantification for robust modeling. Scientific communication, including publications & conference
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within the energetics field. Whilst many reactive burn models have been developed to simulate this behaviour, they are generally designed for ideal explosives and are mostly engineering models fitted
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modelling and simulation techniques and software packages would be an advantage. Programming skills in languages such as Python, C++, MATLAB, are desirable, as is an awareness of machine learning or other AI
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to High-Fidelity Simulations – The project will use OpenFAST, FAST.Farm, and Digital Twin simulations for AI model validation. The student will have the opportunity to join a vibrant community and team
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. The research will combine computational modelling, experimental validation, and machine learning techniques to develop a predictive phenomenological PAC model. The successful applicant will develop and apply
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simulations, exploring novel aspects of numerical modelling and expanding the computational mechanics capabilities of the group. This project offers the opportunity to join a vibrant research group and